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Mike Perkins; Jasper Roe; Darius Postma; James McGaughran; Don Hickerson – Journal of Academic Ethics, 2024
This study explores the capability of academic staff assisted by the Turnitin Artificial Intelligence (AI) detection tool to identify the use of AI-generated content in university assessments. 22 different experimental submissions were produced using Open AI's ChatGPT tool, with prompting techniques used to reduce the likelihood of AI detectors…
Descriptors: Artificial Intelligence, Student Evaluation, Identification, Natural Language Processing
Eaton, Sarah Elaine; Crossman, Katherine; Behjat, Laleh; Yates, Robin Michael; Fear, Elise; Trifkovic, Milana – Journal of Academic Ethics, 2020
This institutional self-study investigated the use of text-matching software (TMS) to prevent plagiarism by students in a Canadian university that did not have an institutional license for TMS at the time of the study. Assignments from a graduate-level engineering course were analyzed using iThenticate®. During the initial phase of the study,…
Descriptors: Computer Software, Plagiarism, College Students, Engineering Education
Kashian, Nicole; Cruz, Shannon M.; Jang, Jeong-woo; Silk, Kami J. – Journal of Academic Ethics, 2015
Plagiarism is a prevalent form of academic dishonesty in the undergraduate instructional context. Although students engage in plagiarism with some frequency, instructors often do little to help students understand the significance of plagiarism or to create assignments that reduce its likelihood. This study reports survey, coding, and TurnItIn…
Descriptors: Plagiarism, Cheating, Learning Activities, Ethics